CDMRI'13
MICCAI 2013 Workshop on
Computational Diffusion MRI
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Welcome and introduction |
8:45-9:00 |
Challenge | White matter model challenge | 9:00-10:00 |
| 9:00-9:07: Benoit Scherrer, Harvard University, USA | |
| 9:07-9:14: Xinghua Zhu, University of Hong Kong & University of Utah | |
| 9:14-9:21: Mohammad Alipoor, Chalmers University, Sweden | |
| 9:21-9:28: Lin Mu, Zhejiang University, China | |
| 9:28-9:35: Torben Schneider, UCL, UK | |
| 9:35-9:42: Uran Ferizi, UCL, UK | |
| 9:42-10:00: Results & discussion | |
Coffee Break and Posters |
10:00-10:30 |
Keynote Lecture I | Denis Le Bihan, NeuroSpin, France |
10:30-11:30 |
| Diffusion MRI: What can we retrieve from the signal? | |
Keynote Lecture II | Susumu Mori, Johns Hopkins University, USA |
11:30-12:30 |
| Multi-atlas multi-contrast brain parcellation based on diffusion tensor imaging and application to individualized anatomical phenotype analysis | |
Lunch and Posters |
12:30-13:30 |
Oral Session I: | High angular methods |
13:30-14:15 |
| 1.1 |
Non-Negative Spherical Deconvolution (NNSD) for Fiber Orientation Distribution Function Estimation |
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Jian Cheng et al |
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University of North Carolina at Chapel Hill, USA |
| 1.2 |
Diffusion Propagator Estimation Using Radial Basis Functions |
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Yogesh Rathi et al |
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Harvard Medical School, United States |
Oral Session II: | Group studies & statistical analysis |
14:15-15:00 |
| 2.1 |
Statistical Analysis of White Matter Integrity for the Clinical Study of Specifc Language Impairment in Children |
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Emmanuel Vallée et al |
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Inria, INSERM, France |
| 2.2 |
Estimating Uncertainty in White Matter Tractography Using Wild Non-Local Bootstrap |
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Pew-Thian Yap et al |
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University of North Carolina, USA |
Coffee Break and Posters |
15:00-15:30 |
Oral Session III: | Tractography and connectivity |
15:30-17:00 |
| 3.1 |
Fiberfox: An extensible system for generating realistic white matter software phantoms |
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Peter Neher et al |
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German Cancer Research Center, Germany |
| 3.2 |
Uncertainty in Tractography via Tract Confidence Regions |
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Colin Brown et al |
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Simon Fraser University, Canada |
| 3.3 |
A Novel Riemannian Metric for Geodesic Tractography in DTI |
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Andrea Fuster et al |
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Eindhoven University of Technology, Netherlands |
| 3.4 |
Groupwise Deformable Registration of Fiber Track Sets using Track Orientation Distributions |
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Daan Christiaens et al |
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KU Leuven, Belgium |
Closing Remarks |
17:00-17:15 |
| 1 |
Choosing a Tractography Algorithm: On the Effects of Measurement Noise
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Andre Reichenbach et al
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University of Leipzig, Germany
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| 2 |
Comparing Simultaneous Multi-slice Diffusion Acquisitions
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Yogesh Rathi et al
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Harvard Medical School, United States
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| 3 |
The Diffusion Dictionary in the Human Brain is Short: Rotation Invariant Learning of Basis Functions
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Marco Reisert et al
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University Medical Center Freiburg, Germany
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| 4 |
Effect of Data Acquisition and Analysis Method on Fiber Orientation Estimation in Diffusion MRI
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Bryce Wilkins et al
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University of Southern California, USA
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| 5 |
Groupwise registration for correcting subject motion and eddy current distortions in diffusion MRI using a PCA based dissimilarity metric
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Wyke Huizinga et al
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Erasmus MC, Netherlands
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| 6 |
Fiber Based Comparison of Whole Brain Tractographies with Application to Amyotrophic Lateral Sclerosis
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Gali Zimmerman-Moreno et al
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Tel Aviv University, Israel
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| 7 |
A Framework for ODF Inference by using Fiber Tract Adaptive MPG Selection
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Hidekata Hontani et al
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Nagoya Institute of Technology, Japan
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| 8 |
A quantitative evaluation of errors induced by reduced field-of-view in diffusion tensor imaging
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Jan Hering et al
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German Cancer Research Center, Germany
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| 9 |
Model-based super-resolution of diffusion MRI
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Alexandra Tobisch et al
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University College London, UK
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